Using software to solve complex problems by analyzing data—known as algorithmic decision-making—offers incredible potential for the public and private sectors to operate more effectively, efficiently, and equitably. For example, the technology has helped streamline wait lists for life-saving organ transplants, improve policing by predicting crime hotspots, and better target charitable giving to the poorest households in rural Kenya.
Despite these benefits, skeptics argue algorithmic decision-making will be inherently exploitative, discriminatory, or simply unreliable, and thus in need of greater government oversight. But countless real-world examples of algorithms unlocking tremendous social and economic benefits indicate otherwise: algorithms can be more effective and less biased than humans when it comes to making important decisions.
Join the Center for Data Innovation for a panel discussion about how public and private sector leaders are using algorithms to make better decisions and what an increasingly data-driven world means for the future of algorithmic decision-making.
Date and Time:
- Tuesday, November 17, 2015 from 9:00 AM – 10:30 AM (EST)
- 1101 K St NW, Suite 610, Washington, DC, 20005
- Courtney Bowman, Co-Director of Privacy and Civil Liberties Engineering, Palantir Technologies
- Madeleine Clare Elish, Researcher, Intelligence and Autonomy Initiative, Data & Society
- Greg Godbout, Chief Technology Officer and U.S. Digital Services Lead, Environmental Protection Agency
- Joshua New, Policy Analyst, Center for Data Innovation (Moderator)
- Bob Sutor, Vice President of Business Solutions and Mathematical Sciences, IBM Research